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With stricter pass-by norms, reducing engine noise radiation is becoming more important. Adding ribs to improve stiffness is one efficient approach to achieve this goal. This paper performs the optimization of ribs which are added on the surface of an inline six-cylinder engine block. The ribs are placed orthogonally. For the optimization, optimization variables are set up to update the dimensions of the ribs in each iteration. The limits of the size changes are defined by the optimization constraints. The overall sound power radiated from the engine block surface between 500Hz and 1450Hz is chosen as the optimization objective. In each iteration, the radiated sound power is obtained by numerical analysis of a fully coupled structural-acoustic model, while the FEM (finite element method) is adopted for calculating the structural response and BEM (boundary element method) is used to compute the noise radiation from the engine block surface.

Welding processes are complex in nature. They affect the mechanical properties of a weldment in and around the welding joint (in the heat affected zone: HAZ), causing deformation and inducing high level of residual stress and plastic strain which are detrimental to the weldment performance. After welding some materials soften while others harden in the heat affected zone, depending on the process heat input, the thickness of the material and its chemical composition. Traditionally, finite element (FE) performance analyses (crash, rupture, fatigue, static and dynamic tests) of weldments are performed without accounting for the effects of welding processes and as such the real performance of a weldment is not accurately predicted. On one hand, if base material properties are used to represent a weldment which hardens in the heat affected zone, the performance analysis results would be too conservative which would hinder/limit potential weight reduction strategies.

A Hybrid method that rigorously couples Statistical Energy Analysis (SEA) and Finite Element Analysis (FEA) has been used to predict interior noise levels in a trimmed vehicle due to broadband structure-borne excitation from 200Hz to 1000Hz. This paper illustrates how the Hybrid FE-SEA technique was applied to successfully predict the car response by partitioning the full vehicle into stiff components described with FE and modally dense components described with SEA. Additionally, it is demonstrated how detailed local FE models can be used to improve SEA descriptions of car panels and couplings. The vibration response of the untrimmed body-in-white is validated against experiments. Next, the radiation efficiency and vibration response of bare and trimmed vehicle panels are compared against reference numerical results. Finally, interior noise levels in bare and trimmed configurations are predicted and results from a noise path contribution analysis are presented.

An existing system-level Statistical Energy Analysis (SEA) model of an enclosed operator station (cab) for a combine-harvester was improved through component-level analyses using Finite Element (FE) and hybrid FE-SEA methods. At mid to high audio frequencies, airborne transmission of machine noise is a dominant path for the cab. An SEA model was created for the cab using the VA One product. When model results were validated against experimental data derived from three idealized insonification load cases, the original model did not compare well with the measured data. The structural panels used in the cab feature various non-uniform cross-sections and varying radii of curvature. The former are not appropriately modeled with standard beam stiffeners, and the latter must be accounted for by some average curvature. Geometrically accurate Finite Element (FE) models of the panels were employed to estimate parameters including effective material stiffness, and effective material density.

A model of a tractor cab was built using Statistical Energy Analysis (SEA) best practices. In this paper, it is shown how this model was correlated using p/Q transfer functions measured in the lab with a volume velocity source. After correlation, the model was excited using acoustic loads measured during tractor operation. It was found that the data predicted by the model is in good agreement with the data measured inside the cabin during this test. It was concluded that SEA can be used as an engineering tool to predict the behavior under many different conditions and can be used to guide the development process.

Electric and Hybrid vehicles have standards for emitting enough noise to reduce danger and risk to pedestrians when operating at low speeds. Simulation can help to support development and deployment of these systems while avoiding a time-consuming, test-based approach to design these AVAS (Acoustic Vehicle Alerting System) warning systems. Traditionally, deterministic simulation methods such as Finite Element Method (FEM) and Boundary Element Method (BEM) are used at low frequencies and statistical, energy-based methods such as Statistical Energy Analysis (SEA) are used at high frequencies. The deterministic methods are accurate, but computationally inefficient, particularly when the frequency increases. SEA is computationally efficient but does not capture well the physics of exterior acoustic propagation. An alternative method commonly used in room acoustics, based on geometrical or ray acoustics, is “Ray Tracing” and can be used for sound field prediction.

Finite element analysis (FEA) is commonly used in the automotive industry to predict low frequency NVH behavior (<150 Hz) of structures. Also, statistical energy analysis (SEA) framework is used to predict high frequency (>400 Hz) noise transmission from the source space to the receiver space. A comprehensive approach addressing the entire spectrum (>20 Hz) by taking into account structure-borne and air-borne paths is not commonplace. In the works leading up to this paper a hybrid methodology was employed to predict structure-borne and air-borne transfer functions up to 1000 Hz by combining FEA and SEA. The dash panel was represented by FE structural subsystems and the noise control treatments (NCTs) and the pass-throughs were characterized via testing to limit uncertainty in modeling. The rest of the structure and the fluid spaces were characterized as SEA subsystems.